Automatic Detection of Buried Mn-crust Layers Using a Sub-bottom Acoustic Probe from AUV Based Surveys

A method for estimating the thickness of sediments covering buried layers of deep sea Cobalt-rich Manganese Crusts (Mn-crusts) from acoustic sub-bottom sonar data, recorded using an Autonomous Underwater Vehicle (AUV), is described. The acoustic data is analyzed with a combination of image and signal processing techniques to identify the optimal reflections coming from the seafloor and the buried layer. The method is applied to data collected from a field experiment and the results were validated using core samples from the same area; showing a high match. By including buried layers into volumetric estimation of Mn-crust deposits, resource potential of seafloor areas can be determined with better accuracy.